Efficient Approximate Bayesian Inference
Videos from BIRS Workshop
Tamara Broderick, Massachusetts Institute of Technology
Monday Mar 10, 2025 10:32 - 11:01
Black Box Variational Inference with a Deterministic Objective: Faster, More Accurate, and Even More Black Box
Diana Cai, Flatiron Institute
Monday Mar 10, 2025 11:02 - 11:16
Batch and match: score-based approaches to black-box variational inference
Marusic Juraj, Columbia University
Monday Mar 10, 2025 11:17 - 11:28
Black-Box VI estimates the gradient by sampling. Is it differentially private by default?
Camila de Souza, University of Western Ontario
Monday Mar 10, 2025 13:07 - 13:23
Clustering Functional Data via Variational Inference
Chengqian Xian, University of Waterloo
Monday Mar 10, 2025 13:25 - 13:42
Fast Variational Bayesian Inference for Survival Data Using Log-Logistic Accelerated Failure Time Models
Ana Carolina da Cruz, Western University
Monday Mar 10, 2025 13:43 - 13:58
Variational Bayes for Basis Function Selection for Functional Data Representation with Correlated Errors
Shrijita Bhattacharya, Michigan State University
Monday Mar 10, 2025 14:33 - 14:49
Variational Inference Aided Variable Selection For Spatially Structured High Dimensional Covariates
Gonzalo Mena, Carnegie Mellon University
Monday Mar 10, 2025 14:50 - 15:04
Approximate Bayesian methods for pseudo-time inference based on relaxed permutations
Lydia Gabirc, Arizona State University
Monday Mar 10, 2025 15:32 - 15:48
Addressing Antidiscrimination with Variational Inference
Daniel Andrade, Hiroshima University
Monday Mar 10, 2025 19:32 - 20:00
Stabilizing training of affine coupling layers for high-dimensional variational inference
Jin Yongshan, Hiroshima University
Monday Mar 10, 2025 20:00 - 20:12
Low-Rank Parameterization for Efficient Bayesian Neural Networks
Trevor Campbell, University of British Columbia
Tuesday Mar 11, 2025 09:01 - 09:32
Making Variational Inference Work for Statisticians: Parallel Tempering with a Variational Reference
Ryan Giordano, UC Berkeley
Tuesday Mar 11, 2025 09:33 - 09:49
Targeted simulation--based inference for efficient posterior marginal estimation
Jonathan Huggins, Boston University
Tuesday Mar 11, 2025 09:49 - 10:07
Random kernel MCMC
Christian Andersson Naesseth, University of Amsterdam
Tuesday Mar 11, 2025 10:32 - 10:46
SDE Matching: Scalable Variational Inference for Latent Stochastic Differential Equations
Yixin Wang, University of Michigan
Tuesday Mar 11, 2025 10:47 - 11:04
Posterior Mean Matching: Generative Modeling through Online Bayesian Inference
Krishnakumar Balasubramanian, University of California Davis
Tuesday Mar 11, 2025 11:04 - 11:33
Improved rates for Stein Variational Gradient Descent
Cheng Zhang, Peking University
Tuesday Mar 11, 2025 13:26 - 13:46
Particle-based Variational Inference with Generalized Wasserstein Gradient Flow
Yian Ma, University of California, San diego
Tuesday Mar 11, 2025 13:46 - 14:01
Reverse diffusion Monte Carlo
Zuheng Xu, University of British Columbia
Tuesday Mar 11, 2025 14:01 - 14:18
Variational flows with MCMC convergence
